AndreaBozzo/ceres-open-data-index huggingface dataset:
Simulated future land cover maps according to different change scenarios, Nan Province, Thailand

[Lien vers la fiche source] This dataset holds the results of different simulations of land cover changes over Nan Province, Thailand, up to 2030. ESA global land cover maps (1992-2015) were used as initialization maps (ESA, 2017). A land-cover (LC) change model was constructed from 1992-2015 maps. Three future land-use scenarios in 2030 (Trisurat et al., 2020) were used to simulate future land cover maps (2016-2030), using the Ocelet modelling platform (ocelet.org). Simulated 2019 land cover maps were compared with a recent LC map of Saen Thong district, Nan province, derived from Sentinel-2 satellite time series. The obtained future land cover maps are intended to study the spread of some common infectious diseases (ANR FutureHealthSEA project: predictive scenarios of health in Southeast Asia, linking land use and climate change to infectious diseases).
Itasy, Vakinankaratra - Madagascar - 2023 - Land cover reference spatial database

[Lien vers la fiche source] This reference database in vector format (ESRI shape format) is organised according to a multi-level nomenclature. It is used to train an image classification algorithm with a view to producing land use maps for the Itashy and Vakinankaratra regions as part of the DINAAMICC project. Each GPS point was converted into a polygon by digitising the boundaries of the corresponding plot on the Google Satellite background and/or the mosaic of Spot 6/7 images acquired in 2022 and 2023 during the growing season. In addition, other polygons were digitised by photo-interpretation of the images. The database covers the entire study area in order to be representative of existing crop types and perennial structures. The final database contains 3726 polygons.
Carte de la sole bananière - 1997 - Guadeloupe

[Lien vers la fiche source] Après les cyclones Iris, Luis et Marylin de la fin d'année 1995 qui faisaient suite à la tempête Debby de 1994, de profondes modifications sont intervenues dans le paysage bananier. Ce projet avait pour objectif de pouvoir disposer pour la première fois en Guadeloupe d'une cartographie à grande échelle ( 1/5 000eme ) du parcellaire bananier et par la suite d'une estimation statistique très précise des superficies. Les travaux ont été menés à partir d'une mission aérienne spécifique au 1/20 000 réalisée en 1996 et ont permis de mesurer et positionner à 1m près toutes les parcelles de taille supérieure ou égale à un quart d'hectare puis d'estimer les superficies avec une erreur globale maximale de 3% soit 150 ha. Une enquête terrain complémentaire a été effectuée en 1997 en collaboration avec les SICA, les Groupements de Producteurs et la Chambre d'Agriculture de Guadeloupe. Cette grande précision à la fois cartographique et statistique a pu être obtenue par l'utilisation des techniques de la photogrammétrie pour restituer les surfaces projetées, les points cotés et les courbes de niveau, mais aussi grâce à la création d'un Modèle Numérique de Terrain (MNT) qui a permis de caractériser chaque parcelle par sa pente et de calculer les surfaces développées réellement cultivées (le quart des surfaces est cultivé sur des pentes supérieures à 30%). De plus, afin d'enregistrer les modifications intervenues après la mission aérienne, une mise à jour du parcellaire a été effectuée en 1997 à l'aide d'un système GPS fonctionnant en mode différentiel grâce à l'installation pour la première fois en Guadeloupe d'une station de référence en poste fixe à la station de recherches du CIRAD. Les produits cartographiques établis dans le système UTM 20 sont constitués de cartes A0 au 1/75 000 et au 1/25 000 donnant les limites des parcelles de bananes classées en 3 catégories (variétés d'exportation, plantains et parcelles à replanter) ainsi que de supports d'enquêtes au 1/10 000 ou au 1/5 000. Cette classification est disponible sur les cartes dont les liens figurent ci-dessous. Le fichier diffusé ici est au format vecteur ESRI Shape. La projection est de l'UTM 20 Nord correspondant au code EPSG 32620.
TRANSMAT tables data

[Lien vers la fiche source] This dataset presents data obtained from manual and automatic extraction of partial n-Ary relations encountered in table forms. The tables were obtained from on documents available on the Science Direct website. The data are related to permeability n-Ary relations, as defined in the TRANSMAT Ontology (https://ico.iate.inra.fr/atWeb/, https://doi.org/10.15454/NK24ID, http://agroportal.lirmm.fr/ontologies/TRANSMAT). The manual annotation was performed following the annotation guide available within this dataset. The tables of ten documents were manually annotated by one annotator and then cross-curated by three annotators. Each folder, one for the manual and one for the automatic annotation, contain one html file per annotated table and one .csv file containing all the data. Each line of the .csv file represent an instance of a partial n-Ary relation. The information available on each annotation are: Doc (the original document), Relation (the relation concept covering the annotated items), Result_Argument (the argument instance that defines the relation), Arguments (a list of all argument instances belonging to the relation instanec), Table (the table name in which the partial relation originated), Caption (the table caption), Segment (the name of the section to which the table belongs), Document (the article title) and DOI (the document DOI)
COVID-19 and media dataset:  Mining textual data according periods and countries (UK, Spain, France)

[Lien vers la fiche source] These datasets contain a set of news articles in English, French and Spanish extracted from Medisys (i‧e. advanced search) according the following criteria: (1) Keywords (at least): COVID-19, ncov2019, cov2019, coronavirus; (2) Keywords (all words): masque (French), mask (English), máscara (Spanish) (3) Periods: March 2020, May 2020, July 2020; (4) Countries: UK (English), Spain (Spanish), France (French). A corpus by country has been manually collected (copy/paste) from Medisys. For each country, 100 snippets by period (the 1st, 10th, 15th, 20th for each month) are built. The datasets are composed of: (1) A corpus preprocessed for the BioTex tool - https://gitlab.irstea.fr/jacques.fize/biotex_python (*.txt) [~ 900 texts]; (2) The same corpus preprocessed for the Weka tool - https://www.cs.waikato.ac.nz/ml/weka/ (*.arff); (3) Terms extracted with BioTex according spatio-temporal criteria (*.csv) [~ 9000 terms]. Other corpora can be collected with this same method. The code in Perl in order to preprocess textual data for terminology extraction (with BioTex) and classification (with Weka) tasks is available. A new version of this dataset (December 2020) includes additional data: - Python preprocessing and BioTex code [Execution_BioTex‧tgz]. - Terms extracted with different ranking measures (i‧e. C-Value, F-TFIDF-C_M) and methods (i‧e. extraction of words and multi-word terms) with the online version of BioTex [Terminology_with_BioTex_online_dec2020.tgz],
Valorcarn-TETIS: Terms extracted with Fastr (free extraction)

[Lien vers la fiche source] Text-Mining: Terms extracted with FASTR tool (free extraction) from "Valorcarn Corpus" ([http://dx.doi.org/10.18167/DVN1/7YTQGQ]). -- Valorcarn Project (2015-2017) [project supported by GloFoodS program (INRA-Cirad)]. Topic: Mining of scientific documents for identification of process that enables to reduce losses and waste.
Valorcarn-TETIS: Candidates for OTR (Ontological and Terminological Resource)

[Lien vers la fiche source] Text Mining: The different terms extracted by text-mining approaches are candidates for an OTR (Ontological and Terminological Resource) associated to Valorcarn Project. -- Valorcarn Project (2015-2017) [project supported by GloFoodS program (INRA-Cirad)]. Topic: Mining of scientific documents for identification of process that enables to reduce losses and waste.
Valorcarn-TETIS: Variations of terms extracted with Fastr (driven extraction)

[Lien vers la fiche source] Text mining: Extraction of variations of term extraction. Input: (1) list of terms, (2) corpus ("Valorcarn Corpus" - [http://dx.doi.org/10.18167/DVN1/7YTQGQ]) For instance, with "biltong samples", we obtain "biltong spice sample", "samples to produce biltong", etc. -- Valorcarn Project (2015-2017) [project supported by GloFoodS program (INRA-Cirad)]. Topic: Mining of scientific documents for identification of process that enables to reduce losses and waste
Valorcarn-TETIS: Fusion of terms extracted with Biotex and Fastr

[Lien vers la fiche source] Text-Mining: Fusion of terms extracted with Biotex and Fastr from "Valorcarn Corpus" ([http://dx.doi.org/10.18167/DVN1/7YTQGQ]). -- Valorcarn Project (2015-2017) [project supported by GloFoodS program (INRA-Cirad)]. Topic: Mining of scientific documents for identification of process that enables to reduce losses and waste.
High resolution map of plant available water content for Burkina Faso, derived from iSDA Africa 30m soil properties maps using USDA Rosetta3 model

[Lien vers la fiche source] Purpose: The purpose of this dataset is to provide a high resolution map of available water content for Burkina Faso derived from 30m soil properties maps using the iSDA Africa dataset and the USDA Rosetta3 model. The map can be used to notably support spatialized crop simulation models to determine potential crop yields across West Africa. Nature and extent of data: The dataset consists of a high resolution map of plant available water content derived from four soil property datasets from iSDA Africa. The soil properties include sand, clay, silt and fine-earth bulk density, and were predicted at a 30m resolution for 0-20 cm and 20-50cm depth intervals. The USDA Rosetta model was used to compute soil water retention properties from four iSDA layers (sand, clay, silt content, and fine-earth bulk density), including the van Genuchten parameters of residual water content, saturated water content, 'alpha' shape parameter, 'n' shape parameter, and saturated hydraulic conductivity. From these parameters, the volumetric water content at field capacity and permanent wilting point was computed using the van Genuchten-Mualem model. The output map has been filled with nearest neighbor interpolation where NaN values were present. Finally, available water content integrated over the soil profile down to 50cm and to the bedrock depth was calculated. Location and coverage: The dataset covers the country of Burkina Faso in West Africa at a 30m resolution. Temporal scope: The dataset was created using soil property data and models from iSDA Africa and USDA Rosetta3, respectively, and covers the temporal scope of the original datasets. Archive formats / unzipping: Some of the archive files are separated in multiple parts, as indicated by their numeral file extensions (i.e. *.001, *.002, etc). To unzip these files, please consider using an unzipping software such as 7zip, that will manage file concatenation and unzipping given that all parts are stored under the same folder in your file system.
High resolution map of plant available water content for Senegal, derived from iSDA Africa 30m soil properties maps using USDA Rosetta3 model

[Lien vers la fiche source] Purpose: The purpose of this dataset is to provide a high resolution map of available water content for Senegal and Gambia derived from 30m soil properties maps using the iSDA Africa dataset and the USDA Rosetta3 model. The map can be used to notably support spatialized crop simulation models to determine potential crop yields across West Africa. Nature and extent of data: The dataset consists of a high resolution map of plant available water content derived from four soil property datasets from iSDA Africa. The soil properties include sand, clay, silt and fine-earth bulk density, and were predicted at a 30m resolution for 0-20 cm and 20-50cm depth intervals. The USDA Rosetta model was used to compute soil water retention properties from four iSDA layers (sand, clay, silt content, and fine-earth bulk density), including the van Genuchten parameters of residual water content, saturated water content, 'alpha' shape parameter, 'n' shape parameter, and saturated hydraulic conductivity. From these parameters, the volumetric water content at field capacity and permanent wilting point was computed using the van Genuchten-Mualem model. The output map has been filled with nearest neighbor interpolation where NaN values were present. Finally, available water content integrated over the soil profile down to 50cm and to the bedrock depth was calculated. Location and coverage: The dataset covers the countries of Senegal and Gambia in West Africa at a 30m resolution. Temporal scope: The dataset was created using soil property data and models from iSDA Africa and USDA Rosetta3, respectively, and covers the temporal scope of the original datasets. Archive formats / unzipping: Some of the archive files are separated in multiple parts, as indicated by their numeral file extensions (i.e. *.001, *.002, etc). To unzip these files, please consider using an unzipping software such as 7zip, that will manage file concatenation and unzipping given that all parts are stored under the same folder in your file system. Changelog: * v1 : first submission * v2 : maps have been clipped along the coastline to remove unwanted production artifacts
Banana, sugar cane and market gardening plots, Guadeloupe, 1987

[Lien vers la fiche source] A map of banana, sugarcane and market gardening plots was produced from scanned paper maps of Guadeloupe in 1987 published by the French Agriculture and Forestry Department. Paper maps have been digitized and georeferenced to be integrated into a Geographic Information System environment. Then, vectorization tools have been used to convert the scanned images (TIF format) into vector-based feature layers (shapefile format) (software: ESRI ArcMap and ArcScan Extension, Redlands, CA, USA). Une carte des parcelles de culture de banane, de canne à sucre et de maraîchage a été produite à partir de cartes papier scannées de la Guadeloupe en 1987 publiées par la Direction de l'Agriculture et de la Forêt (DAF). Les cartes papiers ont été scannées et géoréférencées pour être intégrées dans un Système d'Information Géographique. Des outils de numérisation ont ensuite été utilisés pour convertir les images scannées (format TIF) en couches vectorielles (format shapefile) (logiciel : ESRI ArcMap and ArcScan Extension, Redlands, CA, USA)
Madagascar rural observatory surveys, a longitudinal dataset on household living conditions 1995-2015: microdata and documentation

[Lien vers la fiche source] A Rural Observatory System (ROS) was established in Madagascar to address the lack of socioeconomic data on rural areas. It collected, analyzed, and disseminated data to help formulate and evaluate development policies. From 1995 to 2014, the ROS surveyed a total of 26 areas. The ROS methodology involved annual household panel surveys using consistent questionnaires supplemented by modules covering new themes and enriched questions tailored to specific contexts. Qualitative community surveys were used to understand local features and dynamics. The site selection combined quantitative and qualitative insights to reflect the diversity of Madagascar's rural challenges. Quality control was comprehensive, with measures such as limiting the number of daily surveyor interviews and daily field supervision. By making this data available for 21 consecutive years, along with documentation, metadata, and code with analysis examples, we aim to facilitate their discovery, assessment, and understanding by researchers, policymakers, and social organizations. To our knowledge, this is the only available data for an in-depth analysis of the situation and trends in the rural areas of Madagascar.
Initiation to R for survey data analysis : an example with the analysis of crop diversity in Subsaharan Africa

[Lien vers la fiche source] This initiation to survey data analysis with R was designed to be offered at a multi-stakeholders workshop within the EWA-BELT H2020 EU project (grant n°862848 ; [ewabelt.eu]). This training had two main objectives : 1. The first objective was to do an initiation to data handling, cleaning, formatting and visualization with R from the very bases for people who never used R. This initiation to the basic concepts of R was also designed for people who already worked with R for statistical analysis but who did not have an introduction to the basics of R syntax and to the tidyverse syntax. 2. The second objective of this training was for partners to get familiar with the data collected during a survey about the diversity and valued of 'Neglected and Under-utilized Species' (NUS) in the frame of the EWA-BELT project. In line with the first objective of the course, this training content can be used by any trainer for an initiation to R for very beginners wanting to be introduced to survey data cleaning, formatting and visualization or for people already introduced to R but who want to update there bases in R.
797 sequences of plant ns Lipid Transfer Protein (fasta file)

[Lien vers la fiche source] This is the list of all nsLTP sequences used for our work "Comprehensive classification of the plant non-specific lipid transfer protein superfamily towards its Sequence – Structure – Function analysis". It might be useful for any studies in phylogeny (this is the largest dataset used in a phylogeny study to date) or sequence-structure-function relationships. The sequences are named as follows : 3 digit number (from 001 to 800 - from internal classification) nsLTP Type (if available and as stated by initial authors) organism 5 letters code Database identifier (identifier form the database the sequence was retrieved from) Sequence number 526, 600 and 693 were removed during the study (redundancy)
Co-products management practices in agro-pastoral farms in Burkina Faso

[Lien vers la fiche source] This data table in Excel provides information from a survey concerning the management of crops co-products (CCP: straws, tops, stalks) and animal co-products (CCP: Dung) in agro-pastoral farms in western Burkina Faso in 2021. These data were used for writing a paper entitled ''Recycling crop and animal co-products on agro-pastoral farms for the agroecological transition: more than 60% potentially recoverable in western Burkina Faso". The Excel file contains 10 sheets: 1) Map of the study sites; 2) Pre-survey data (188 farms); 3) CCP and ACP management data for the 60 farms; 4) Data from table 1 of the draft article; 5) Principal Component Analysis; 6) Hierarchical Ascending Classification ; 7) ANOVA on the PCA variables; 8) ANOVA on the structure variables of the 60 farms; 9) Data from tables 2, 3 and 4 of the draft article; 10) Parameters
Food supply chains sustainability assessment of the mango sector in Burkina Faso

[Lien vers la fiche source] This dataset is joint with the scientific publication named "A Multiple food supply chains sustainability assessment of the mango sector in Burkina Faso" which details the challenges of the mango sub-sectors in Burkina Faso, the contribution of the Value Chain to economic growth and the analysis of its inclusiveness, the analysis of its social sustainability, and the analysis of its environmental sustainability.
Exploitations cotonnières au nord de la Côte d'Ivoire en 2013-14

[Lien vers la fiche source] Capture of the characteristics of farms in Northern Cote d'Ivoire in 2014 two years after the civil war had ended up. Characteristics were captured through a survey implemented in July-August 2014, in terms of farm structure, farm families, cropping systems. The survey was implemented along farm heads (men) as well as their wives.
Farms in Cabo-Delgado province at the turn to a new century

[Lien vers la fiche source] Survey along 900 farms in the 1999-2000 cropping season, growing cotton or not, to provide information on the characteristics of the farms, farmers and their families, as well as the crops grown on a sample of plots. The survey informs on the use of fertilizers and insecticides and the recourse to extra-family labour. It gives an insight on farmers' possession of bicycles and radio sets a few years after the civil peace was re-established.
Antananarivo - Madagascar - Land use change map between 2003 and 2017

[Lien vers la fiche source] Land use map, in ESRI shapefile format, displaying the evolution of artificial spaces in Antananarivo agglomeration (Madagascar capital) during 2003 to 2017 period. This map is the result of remote sensing processing of satellite images. Spot5 images acquired on February 14 and July 4, 2003 were used. Access to the images was granted by CNES via the ISIS program. The treatment consisted in using the land use map extracted on the same study zone in 2017 (Cf. reference below) as a mask and checking on the old images the evolution of the built spaces. We tried to measure agricultural areas evolution during the same period but the robustness of the results is not satisfactory because of the difficulty in distinguishing between agricultural and natural areas on 2003 images. Result validation was carried out using a reference database created by photo-interpretation by an independent operator. The overall accuracy of the map is 91.63% and kappa index is 0.88.
Standardising field-based assessment of invasion degree: a case study in two habitats of Reunion Island

[Lien vers la fiche source] The data comprise presence, cover and invasion rates of alien plant species and native plant cover in lowland tropical forest and subalpine vegetation (Mare Longue and Piton de Caille sites) in La Reunion. Abundance and diversity values are quantified among three vegetation strata (herbaceous, shrub and tree).
Essai intensification du maïs au Nord Cameroun (2013)

[Lien vers la fiche source] Essais mis en place chez des producteurs dans deux grappes de villages du Nord Cameroun en 2013 dans l'objectif d'étudier la faisabilité de l'intensification de la culture du maïs. Des résultats d'analyses de sols sur chaque essai sont parvenus après ces valorisations qui peuvent donner lieu à d'autres interprétations
Health state of the tunisian population evaluated by the Tunisian Health Examination Survey (THES-2016): data and documentations

[Lien vers la fiche source] The Tunisian Health Examination Survey (THES-2016) is a representative national survey conducted by the [National Institute of Health-Tunisia] with the support of the [Ministry of Health-Tunisia] and the [World Health Organization (WHO) ], in collaboration with the [National Office for Family and Population - Tunisia], the Research laboratory in Epidemiology and Prevention of Cardiovascular Diseases - Tunisia and the Tunisian Society of Endocrinology Diabetes and Metabolic Diseases. The objective of this survey is to analyze the state of health of the population, its determining factors as well as the consequences of illnesses and the use of health care services. Data collection in the field took place between March 9, 2016 and June 4, 2016 by administering two questionnaires: * Household questionnaire: covered the usual demographic parameters: age, sex and rural-urban residence as well as access to water and sanitation, access to necessary care, use outpatient and inpatient care, health insurance coverage, responsiveness of the health care system, total and household health expenditure and death registration coverage. * Individual questionnaire for people aged 15 and over: focused on risky behavior (alcohol, tobacco, etc.), overall health as perceived by respondents and medical history. Anthropometric and functional measurements as well as blood tests were also carried out. Women of childbearing age were also asked about their reproductive health state and the vaccination coverage of their children under 5 years old. We had the agreement of 5079 households to participate in the survey from which we were able to obtain information on the state of health of 9212 individuals aged 15 and over and randomly selected among the people living in the households visited (1 Male, 1 Female from each household).